Review

Metagenomics and the molecular identification of novel viruses

Nicholas Bexfield a,*, Paul Kellam b

a Department of Veterinary Medicine, University of Cambridge, Cambridge CB3 0ES, UKb The Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK

* Corresponding author. Tel.: +44 1223 765631.E-mail address: nb289@cam.ac.uk (N. Bexfield).

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Abstract

There has been rapid recent development in methods of identifying and characterising

viruses associated with animal and human disease. These methodologies, commonly based on

hybridisation or PCR techniques, are combined with advanced sequencing techniques termed

‘next generation sequencing’. Allied advances in data analysis, including the use of

computational transcriptome subtraction, have also had an impact in the field of viral

pathogen discovery. This review details these molecular detection techniques, discusses their

application in viral discovery and provides an overview of some of the novel viruses

discovered. The problems encountered in attributing disease causality to a newly identified

virus are also considered.

Keywords: Metagenomics; Virus discovery; Animals; Computational transcriptome

subtraction; Hybridisation

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Introduction

Given that animal pathogens, in particular viruses, are considered to be a significant

source of emerging human infections (Cleaveland et al., 2001), the identification and optimal

characterisation of novel viruses affecting both domestic and wild animal populations is

central to protecting both human and animal health. Recent outbreaks of human infection

caused by influenza H7N7 virus, transmitted from poultry (Koopmans et al., 2004) and H1N1

virus, transmitted from pigs (Dawood et al., 2009), are cases in point, highlighting the need

for ongoing, vigilant epidemiological surveillance of such pathogens in animal populations.

Moreover, epidemiological studies strongly suggest that novel infectious agents remain to be

discovered (Woolhouse et al., 2008) and may be contributing to cancer, autoimmune

disorders and degenerative diseases in humans (Relman, 1999; Dalton-Griffin and Kellam,

2009). Yet-to-be-identified viruses may be contributing to the pathogenesis of similar diseases

in animals.

Viruses can be identified by a wide range of techniques. Traditional methods include

electron microscopy, cell culture, inoculation studies and serology (Storch, 2007). While

many of the viruses known today were first identified by these techniques, these methods

have limitations. Many viruses cannot be cultivated in the laboratory and can only be

characterised by molecular methods (Amann et al., 1995); recent years have seen the

increasing use of these techniques in pathogen discovery (Fig. 1). One such approach uses

sequence information from known pathogens to identify related but undiscovered agents

through cross-hybridisation. Examples include microarray (Wang et al., 2002) and subtractive

(Lisitsyn et al., 1993) hybridisation-based methods. Another advance has involved PCR

amplification of the pathogen genome, where there is complete knowledge of the pathogen to

be amplified (conventional PCR), or where this information is limited (degenerate PCR).

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Other PCR methods, such as sequence-independent single primer amplification (SISPA),

degenerate oligonucleotide primed PCR, random PCR and rolling circle amplification, also

have the capacity to detect novel pathogens. Hybridisation and PCR-based methods are more

effective if the sample to be analysed is first enriched for the pathogen, a process achieved by

removing host and other contaminating nucleic acids. The end result of most hybridisation

and PCR methods are amplified products that require definitive identification by sequencing.

Advances in sequencing that have facilitated virus discovery include the arrival of ‘next

generation’ or ‘second generation’ sequencing, which can generate large amounts of sequence

data.

Technological advances have also lead to the development of metagenomics, the

culture-independent study of the collective set of microbial populations (microbiome) in a

sample by analysing the nucleotide sequence content (Petrosino et al., 2009). The different

microorganisms constituting a microbiome can include bacteria, fungi (mostly yeasts) and

viruses. Examples of microbiomes in mammalian biology include the microbial populations

inhabiting the human intestine or mucosal surfaces in health and disease. To date, the study of

the viral microbiome (virome) has been applied to a range of biological and environmental

samples including human (Finkbeiner et al., 2008) and equine (Cann et al., 2005) intestinal

contents, bat guano (Li et al., 2010), sea water (Breitbart et al., 2002; Angly et al., 2006),

fresh water (Breitbart et al., 2009), hot springs (Schoenfeld et al., 2008) and soil (Fierer et al.,

2007). Early results from a large initiative to describe the humane microbiome associated with

health and disease have been published (Nelson et al., 2010) and such findings, together with

those of other studies, are likely to lead to the discovery of a wealth of previously unknown

viruses.

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This review describes the current molecular techniques available for the detection of

viruses infecting animals and humans. We begin by discussing hybridisation and PCR-based

methods and describe advances that have facilitated the detection of completely novel viruses.

Advances in sequencing methodology and data analysis, such as transcriptome subtraction,

are also appraised. The review concludes with an assessment of the problems encountered

when attempting to establish disease causality with a newly discovered virus.

Hybridisation-based methods

Microarray techniques

Microarrays consist of high-density oligonucleotide probes, or segments of DNA,

immobilised on a solid surface. Any complementary sequences (labelled with fluorescent

nucleotides) in a test sample hybridise to the probe on the microarray. The results of

hybridisation are detected and quantified by fluorescence-based methods, allowing the

relative abundance of nucleic acid sequences in a sample to be determined (Clewley, 2004).

Two types of microarray techniques are commonly used for virus identification. The

first uses short oligonucleotide probes, sensitive to single-base mismatches, to detect or

identify known, or sub-types of known, viruses. Such a technique has been used to

discriminate human herpesviruses (Foldes-Papp et al., 2004). The second type of microarray

method employs long oligonucleotide probes (60 or 70 base pairs, bp) that allow for sequence

mismatches (Wang et al., 2002). Microarray applications have been used in the discovery of

novel animal viruses, such as a coronavirus in a Beluga whale (Mihindukulasuriya et al.,

2008), the bornavirus that causes proventricular dilatation disease in wild psittacine birds

(Kistler et al., 2008) and an enterovirus associated with tongue erosions in bottle-nose

dolphins (Nollens et al., 2009). In human medicine they have been used to characterise the

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severe acute respiratory syndrome coronavirus (SARS-CoV) (Wang et al., 2003) and to

identify novel viruses: coronaviruses and rhinoviruses in human patients with asthma (Kistler

et al., 2007) and cardioviruses in the gastrointestinal tract (Chiu et al., 2008).

Microarray technology is a powerful tool, since it can be used to screen for a large

number of potential pathogens simultaneously (Wang et al., 2002). The method does have

limitations, since the process of interpreting hybridisation signals is not a trivial one, often

involving the empirical characterisation of signals produced by known viruses and the

development of specialised software (Urisman et al., 2005). Furthermore, microarray

techniques utilise probes with a finite specificity for a particular pathogen or small group of

pathogens, so that novel or highly divergent strains or viruses can be difficult to detect. Non-

specific binding of test material to hybridisation probes can also result in loss of test

sensitivity. Despite these limitations, microarrays have proven to be extremely effective in

novel pathogen discovery.

Subtractive hybridisation

This form of hybridisation identifies sequence differences between two related

samples and is based on the principle of removing common nucleic acid sequences from two

samples, while leaving differing sequences intact. Such a process can be applied to any pair of

nucleic acid sources, such as ‘treated’ vs. ‘untreated’ or ‘diseased’ vs. ‘non-diseased’ tissue,

or to samples obtained prior to and after experimental infection (Muerhoff et al., 1997).

Subtractive hybridisation uses two nucleic acid sources termed ‘tester’ and ‘driver’,

with only the tester containing pathogen sequences (Ambrose and Clewley, 2006). DNA in

both the tester and driver nucleic acid is digested by restriction enzymes and adaptors are

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ligated to the DNA fragments from the tester sample only. The two DNA populations are

mixed, denatured and annealed to form three types of molecule: tester/tester, hybrids of

tester/driver and driver/driver. The tester/tester molecules should now be enriched for the

pathogen(s), which are preferentially and exponentially amplified by primers specific for the

adaptors present on both DNA strands. The tester/driver molecules, which contain an adaptor

on only one DNA strand, undergo linear amplification, but are then removed by enzymatic

digestion. The driver/driver molecules have no adaptors and are not amplified. Sufficiently

enriched in this way, the tester sample is sequenced and the pathogen identified.

An example of a subtractive hybridisation method is representational difference

analysis (RDA) (Lisitsyn et al., 1993). Despite its impressive performance in model systems,

RDA has had limited success in the discovery of novel viruses, largely due to the requirement

for two highly matched nucleic acid sources. Restriction enzyme digestion also leads to

increased DNA complexity and the risk of inefficient subtractive hybridisation, a particular

problem with samples containing large amounts of host DNA, such as serum or plasma.

Despite these limitations, RDA has been used to identify the agent causing Kaposi’s sarcoma

(human herpesvirus-8) (Chang et al., 1994), torque teno or transfusion-transmitted virus

(TTV) (Nishizawa et al., 1997) and the hepatitis GBV-A and GBV-B viruses (Simons et al.,

1995b).

PCR based methods

Degenerate PCR

Conventional PCR is frequently used to identify or exclude the presence of a virus in

samples. Given that the method relies on the annealing of specific primers complementary to

the pathogen’s genomic sequence of interest, it is unsuitable for the detection of novel viruses

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with marked sequence differences from the primers. Prior knowledge of the viral sequence is

therefore a prerequisite. An alternative PCR method, degenerate PCR, uses primers designed

to anneal to highly conserved sequence regions shared by related viruses. Since these regions

are almost never completely conserved, primers generally include some degeneracy that

permits binding to all or the most common known variants on the conserved sequence (Rose

et al., 1998). The overall aim is to achieve a balance between covering all possible viral

variants within a family (i.e. primers with high degeneracy) and creating an unwieldy number

of different primers. At high levels of degeneracy, only a small proportion of primers are able

to prime DNA synthesis, whereas a large proportion of the remaining primers will be able to

anneal, but will be refractory to PCR extension because of sequence mismatches. The

maximum level of degeneracy is usually fixed at approximately 256 and degeneracy can be

reduced by using codon usage tables (Wada et al., 1992) and inter-codon dinucleotide

frequencies (Smith et al., 1983).

Degenerate primers are used to detect viruses, including novel viruses, from existing

sufficiently homologous virus families. Such primers have been used in the identification of

pig endogenous retrovirus (PERV) (Patience et al., 1997), numerous macaque

gammaherpesviruses (VanDevanter et al., 1996; Rose et al., 1997), a novel alphaherpesvirus

associated with death in rabbits (Jin et al., 2008) and a novel chimpanzee polyomavirus

(Johne et al., 2005). Novel viruses infecting humans detected using this technique include

hepatitis G virus (Simons et al., 1995a), a hantavirus (Sin Nombre virus) (Nichol et al., 1993),

coronaviruses (Sampath et al., 2005) and parainfluenza viruses 1-3 (Corne et al., 1999).

Sequence-independent single primer amplification

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Sequence-independent amplification of viral nucleic acid (SISPA) avoids the potential

limitations of other methods, particularly the lack of microarray hybridisation due to genetic

divergence from known viruses, the absence of a matched sample for subtractive

hybridisation and where PCR amplification using conventional or degenerate primers fails.

The advantages of these methods are their ability to detect novel viruses highly divergent

from those already known, their relative speed and simplicity of use and their lack of bias in

identifying particular groups of viruses (Delwart, 2007).

SISPA was introduced to identify viral nucleic acid of unknown sequence present in

low amounts (Reyes and Kim, 1991). SISPA was used to first sequence the norovirus genome

from human faeces (Matsui et al., 1991), along with a rotavirus (Lambden et al., 1992) and an

astrovirus (Matsui et al., 1993) infecting humans. Initially, SISPA involved endonuclease

digestion of DNA, followed by directional ligation of an asymmetric adaptor or primer onto

both ends of the DNA molecule (Reyes and Kim, 1991). Common end sequences of the

adaptor allowed the DNA to be amplified in a subsequent PCR reaction using a

complementary single primer.

Due to the low complexity of a viral genome, enzymatic digestion produces a large

amount of a limited number of fragments. After amplification, these are visible as discrete

bands on an agarose gel and can be sequenced and identified (Allander et al., 2001). Since

animal and bacterial genomes are larger and more complex, restriction digestion generates

many different-sized fragments, the amplification of which can result in ‘smears’ on agarose

gel. One of the disadvantages of sequence-independent amplification techniques is the

contemporaneous amplification of ‘contaminating’ host and bacterial nucleic acid. Enriching

methods that reduce such ‘background’ genomic material include filtration, ultra-

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centrifugation, density gradient ultra-centrifugation and enzymatic digestion of non-viral

nucleic acids using DNase and RNase (Delwart, 2007). These techniques take advantage of

the differential protection afforded to the virus genome by nucleocapsids and capsids.

However, since viral nucleic acid, not protected by such capsids, is removed by the

purification process and not amplified, some potential assay sensitivity is lost. Furthermore,

the random nature of the amplification reaction means that great care must be taken to

maintain PCR integrity and prevent cross-contamination.

The original SISPA method therefore has been modified to include steps to detect both

RNA and DNA viruses, to enrich for virus and to remove host genomic and contaminating

nucleic acid (Allander et al., 2001). Novel human and animal viruses detected in clinical

samples using these modified methods include parvoviruses (Allander et al., 2001; Jones et

al., 2005), a coronavirus (van der Hoek et al., 2004), an adenovirus (Jones et al., 2007a), an

orthoreovirus (Victoria et al., 2008), a picornavirus (Jones et al., 2007b) and a porcine

pestivirus (Kirkland et al., 2007).

Degenerate oligonucleotide primed PCR

Degenerate oligonucleotide primed PCR (DOP-PCR) was initially developed for

genome mapping studies (Telenius et al., 1992), but has more recently been modified to

detect viral genomic material (Nanda et al., 2008). DOP-PCR uses primers with a short (four

to six nucleotide) 3’ anchor sequence, which typically occur in nucleic acid every 256 and

4096 bp, respectively, preceded by a non-specific degenerate sequence of six to eight

nucleotides for random priming. Immediately upstream of the non-specific degenerate

sequence, each primer also contains a defined 5’ sequence of 10 nucleotides. Each reaction

includes a mixture of several thousand different primers because of the degenerate sequence.

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At low stringency during the first few DOP-PCR amplification cycles, at least 12 consecutive

nucleotides from the 3’ end of the primer anneal to DNA sequences on the PCR template. In

subsequent cycles at higher stringency, these initial PCR products are amplified further using

the same primer population. DOP-PCR, when followed by sequencing of the product, has the

advantage of facilitating the detection of both RNA and DNA viruses without a priori

knowledge of the infectious agent (Nanda et al., 2008).

Random PCR

Random PCR (Froussard, 1992) is an alternative sequence-independent amplification

technique, which is commonly used to amplify and label probes with fluorescent dyes for

microarray analysis, but has also been used in the identification of novel viruses. Unlike

SISPA, random PCR has no requirement for an adaptor ligation step and, compared with

‘conventional’ PCR, which utilises a pair of complementary ‘forward’ and ‘reverse’ primers

to amplify DNA in both directions, random PCR utilises two different primers and two

separate PCR reactions. The single primer used in the first PCR reaction has a defined

sequence at its 5’ end, followed by a degenerate hexamer or heptamer sequence at the 3’ end.

A second PCR reaction is then performed with a specific primer complementary to the 5’

defined region of the first primer, thus enabling amplification of products formed in the first

reaction.

Random PCR has been used extensively for the detection of both DNA and RNA

viruses and is currently the molecular method most commonly used to identify unknown

viruses. Viruses infecting animals identified using this technique include a dicistrovirus

associated with ‘honey-bee colony collapse disorder’ (Cox-Foster et al., 2007), a seal

picornavirus (Kapoor et al., 2008) and circular DNA viruses in the faeces of wild-living

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chimpanzees (Blinkova et al., 2010). Random PCR has also proved successful in detecting

novel viruses infecting humans, including a parvovirus (Allander et al., 2005), a coronavirus

(Fouchier et al., 2004), a polyomavirus in patients with respiratory tract disease (Allander et

al., 2007), a parechovirus (Li et al., 2009c), a picornavirus (Li et al., 2009b) and a bocavirus

in patients with diarrhoea (Kapoor et al., 2009), a human gammapapillomavirus in a patient

with encephalitis (Li et al., 2009a) and cardioviruses in children with acute flaccid paralysis

(Blinkova et al., 2009).

Rolling circle amplification

Rolling circle amplification (RCA) makes use of the property of circular DNA

molecules, such as plasmids or viral genomes replicating through a rolling circle mechanism.

RCA mimics this natural process without requiring prior knowledge of the viral sequence,

utilising random hexamer primers that bind at multiple locations on a circular DNA template,

and a polymerase enzyme, such as bacteriophage ɸ29 DNA polymerase, with strong strand-

displacing capability, high processivity (approximately 70,000 bases/binding event) and

proof-reading activity (Esteban et al., 1993). When the polymerase enzyme comes ‘full circle’

on a circular viral genome, it displaces its 5’ end and continues to extend the new strand

multiple times around the DNA circle. Random primers can then anneal to the displaced

strand and convert it to double stranded DNA (Dean et al., 2001). By using multiply-primed

RCA, unknown circular DNA templates can be exponentially amplified. The long, double-

stranded DNA products can then be cut with a restriction enzyme to release linear fragments

and sequenced for the full length of the circle.

Although technically more demanding than other methods of sequence-independent

amplification, an RCA approach has facilitated the identification of a novel variant of bovine

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papillomavirus type 1 (Rector et al., 2004b) and novel papillomaviruses in a Florida manatee

(Rector et al., 2004a). This method has also yielded the full genomic sequences of

polyomaviruses (Johne et al., 2006b), an anellovirus (Niel et al., 2005) and circoviruses

(Johne et al., 2006a). Through the use of a combination of RCA and SISPA, nine

anelloviruses found in human plasma and cat saliva have been detected and characterised

(Biagini et al., 2007).

Sequencing methods

Most hybridisation and PCR methods generate products that require definitive

identification by sequencing. One method of achieving this is the commonly used ‘chain

termination method’, often referred to as ‘Sanger’ or ‘dideoxy sequencing’. This method is

based on the DNA polymerase-dependent synthesis of a complementary DNA strand in the

presence of natural 2’-doexynucleotides (dNTPs) and 2’,3’-didoexynucleotides (ddNTPs) that

serve as non-reversible synthesis terminators. A limitation of this technique in terms of virus

identification can be the requirement to clone viral sequences into bacteria prior to

sequencing, although direct sequencing of PCR products can also be employed. When cloning

is performed using this method, host-related bias can occur (Hall, 2007); since only a

relatively limited number of clones can be sequenced, methods to enrich for virus prior to

amplification are required.

Use of the Sanger method has been partially succeeded by ‘next generation’

sequencing technologies that circumvent the need for cloning by using highly efficient in

vitro DNA amplification (Morozova and Marra, 2008). Next generation sequencing

technology includes the 454 pyrosequencing-based instrument (Roche Applied Sciences),

genome analysers (Illumina) and the SOLiD system (Applied Biosystems). This approach

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dramatically increases cost-effective sequence throughput, albeit at the expense of sequence

read-length. Compared to read lengths in the region of up to 900 bp produced by modern

automated Sanger instruments, read lengths of 76-106 bp are generated by Illumina and read

lengths of 250-400 bp are generated using 454 technology. The comparatively short read

length of next generation sequencing technologies is, however, compensated for by the large

number of ‘reads’ generated. Typically, 100 kilobases of sequence data is produced from a

modern Sanger instrument, 454 sequencing is capable of generating up to 400 megabases of

data and Illumina sequencing technology can produce up to 20 gigabases of sequence data per

run (Metzker, 2010).

Bioinformatics

Several approaches have been used to analyse data produced by sequencing methods.

To date, the majority of novel viruses have been discovered using Basic Local Alignment

Search Tool (BLAST)1 programmes that compare detected nucleotide sequences to those in a

data base and rely on the fact that novel viruses usually have homology to known viruses.

However, detecting distant viral relatives or completely new viruses can be problematic. For

instance, a proportion of sequences (5-30%) derived from animal samples by sequence-

independent amplification methods, and an even greater fraction of sequences derived from

environmental samples, do not have nucleotide or amino acid sequences similar to those of

viruses listed in existing databases (Delwart, 2007). However, using these methods, viruses

have been identified that are distantly related to known viruses.

Several approaches can be used to increase the likelihood of identifying virus

sequences, including ‘querying’ translated DNA sequences against a translated DNA

database, since evolutionary relationships remain detectable for longer at the amino acid level

1 See: http://blast.ncbi.nlm.nih.gov/

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1

than at the nucleotide level. The computational generation of theoretical ancestral sequences,

and their subsequent use in sequence similarity searches, may also improve identification of

highly divergent viral sequences (Delwart, 2007). Computational biologists have also

developed new ingenious algorithms and techniques to analyse data produced by next

generation sequencing to aid in the identification of novel viruses (Wooley et al., 2010).

Before viruses are identified, the hybridisation and PCR methods described above

generally require both an initial step to enrich for virus and an amplification step (Fig. 2A).

Enrichment can result in loss of viral nucleic acids, thus reducing test sensitivity, whereas

amplification can generate bias towards a dominant (potentially host-derived) sequence.

Transcriptome subtraction (Weber et al., 2002), a technique for viral discovery that can be

performed without the need for enrichment or amplification, is based on the principle that

genes are transcribed (expressed) to produce mRNA, which then can be converted in vitro to

single stranded complementary DNA (cDNA) (Fig. 2B). The sequencing of this cDNA, rather

than genomic DNA, allows the transcribed portion of the genome to be analysed. In view of

the large number of transcripts present, sequencing is usually performed using next generation

technologies.

The technique works on the assumption that a sample infected with a virus would

contain host and viral transcripts. Host transcript sequences are aligned and subtracted from

public databases; in the case of a human sample, these include reference sequences, such as

the human RefSeq RNA or mitochondrial or assembled chromosome sequences in the

National Centre for Biotechnology Information (NCBI) databases. After aligning and

subtracting human sequences against databases, non-matched virus-enriched sequences will

remain and can be studied further. With the completion of the sequencing of several animal

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genomes, transcriptome subtraction techniques are applicable to a variety of other species and

the possibility exists to use both public databases and subtraction against uninfected control

material.

A transcriptome subtraction method has been used to identify a previously unknown

polyomavirus in human Merkel cell carcinoma (Feng et al., 2008) and to identify an

uncharacterised arenavirus associated with three transplant-related deaths (Palacios et al.,

2008) (see Appendix A: Supplementary material). This technique has the advantage of being

able to identify very small amounts of virus, as in the case of the polyomavirus identified by

Feng et al. (2008), in which only 10 viral transcripts per cell were present. Given that each

cell contains approximately one million host transcripts, only a small proportion of the

cellular RNA is virus-derived. Providing every cell is infected, even at very low levels, ten

million sequence ‘reads’ gives a >99.99% probability of detecting at least one viral sequence

(Fig. 3). Such a large number of reads is readily obtainable using next generation technology

such as the Illumina platform. However the technique does have limitations in that if only 1 in

10 cells is infected, or a sequencing methodology is used which produces only 50,000

sequence reads, the probabilities of detecting viral sequence decrease to approximately 60%

and 5%, respectively.

Identification of viral sequences and proof of causation

While many newly identified viruses infecting animals and humans were initially

found in patients with particular clinical signs or symptoms, most have not been causally

associated with particular diseases. The detection of viruses in such contexts may merely

reflect the presence of a virus in a sample or the ability of a virus to replicate within a

particular diseased environment, rather than the virus directly causing the disease. For

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example, although several infectious agents have been found in samples from human patients

with multiple sclerosis (Challoner et al., 1995; Perron et al., 1997; Thacker et al., 2006),

causal roles in pathogenesis have never been attributed (Munz et al., 2009). Similarly, herpes

simplex virus type-2 (HSV-2) was strongly implicated as the cause of cervical cancer in

humans for many years until human papillomavirus DNA was identified in biopsies (Durst et

al., 1983).

Henle-Koch postulates are a well-known set of criteria that must be fulfilled by a

microorganism for it to be proven as the cause of disease. The ability to culture viruses in

vitro and the detection of antibodies against viruses led to a new proposal for the

demonstration of causality (Rivers, 1937). Advances in technology have resulted in new

challenges to the assigning of causation and sequence based approaches to virus identification

have led to the formulation of guidelines defining the relationship between the presence of

viral sequences and disease (Fredericks and Relman, 1996). Such guidelines have been used

to link hepatitis C virus (HCV) with non-A, non-B hepatitis (Kuo et al., 1989), and human

herpesvirus type 8 with Kaposi’s sarcoma (Moore and Chang, 1995), but are often ignored in

the race to assign significance to virus discovery. In infectious disease research, a balance

must be struck between the prompt identification of highly significant new human pathogens,

such as pandemic swine H1N1 influenza (Dawood et al., 2009), and clearly defining the more

tenuous connection between xenotropic murine leucaemia virus-related virus (XMRV) and

chronic fatigue syndrome (Lombardi et al., 2009). Epidemiological, immunological and

sequence-based criteria should support any proposed link between an infectious organism and

the disease under study. Establishing causality must also involve an appreciation of the full

range of genetic diversity of the viral species, as it is well established that distinct viral

genotypes or even minor genetic variations can result in large changes in viral pathogenicity.

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Conclusions

Viral identification is an ever evolving discipline where new technologies are likely to

have a significant impact over the coming decades. The further development of hybridisation

and PCR-based methods, the increased availability of next generation sequencing,

improvements in transcriptome subtraction methods, continued expansion of viral and animal

genome databases and improved bioinformatic tools will facilitate the acceleration of this

identification process.

Conflict of interest statement

None of the authors of this paper has a financial or personal relationship with other

people or organisations that could inappropriately influence or bias the content of the paper.

Appendix A. Supplementary material

Supplementary data associated with this article can be found, in the online version, at

doi: …

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Figure legends

Fig. 1. A schematic overview of the molecular methods currently available for viral

discovery. Hybridisation methods include microarray and subtractive hybridisation techniques

such as representational difference analysis. PCR-based methods include degenerate PCR,

degenerate oligonucleotide primed PCR (DOP-PCR), sequence-independent single primer

amplification (SISPA), random PCR and rolling circle amplification (RCA).

Fig. 2. Sequence of events in the molecular detection of viruses. (A) Samples processed by

hybridisation or PCR require steps to enrich for virus before amplified products are sequenced

and identified. Enrichment may result in decreased assay sensitivity and amplification can

generate bias towards a dominant sequence. (B) Transcriptome subtraction methods can be

performed without enrichment or amplification with direct sequencing of nucleic acids

extracted from a sample of interest. Subsequent subtraction of resulting sequences from

databases facilitates virus identification.

Fig. 3. Graphic representation of the probability of detecting viral sequences based on the

viral genome-transcript sequence frequency and the number of sequence ‘reads’ generated

(coloured lines).

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